An interior-point trust-region polynomial algorithm for convex quadratic minimization subject to general convex constraints

Authors:
Ye Lu;Ya-Xiang Yuan
Affiliations:
Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, USA;LSEC, ICMSEC, Institute of Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, People's Republic of China
Venue:
Optimization Methods & Software - Dedicated to Professor Michael J.D. Powell on the occasion of his 70th birthday
Year:
2008

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Abstract

An interior-point trust-region algorithm is proposed for minimization of a convex quadratic objective function over a general convex set. The algorithm uses a trust-region model to ensure descent on a suitable merit function. The complexity of our algorithm is proved to be as good as the interior-point polynomial algorithm.